A few weeks ago we invited our users to share about their experience with CULA. While we're still gathering their stories, we decided to go ahead and launch our new Research Papers page so it is easier for you to find papers that have been written about CULA, or make a reference to it.

We'd like to highlight and give special thanks to the Medical Image Processing Group at Institute of Automation, Chinese Academy of Sciences for their paper entitled The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography. Very educational paper! Below is just a section we pulled from the abstract:

The CUBLAS and CULA are two main important and powerful libraries for programming on NVIDIA GPUs. With the help of CUBLAS and CULA, it is easy to code on NVIDIA GPU and there is no need to worry about the details about the hardware environment of a specific GPU.

If you have published a paper, let us know and we will add it to the new section. If you have not yet published your work, but would like to share your experience with CULA, you're welcome to do so. We are putting together case studies on the various applications that are being accelerated with CULA. Your feedback is appreciated by the entire engineering team... they love to hear about it, and they love being challenged... so whether positive or negative, let us know how the software is working for you.